The extraction of Fetal Electrocardiogram (FECG) during labor or prenatal phases of pregnancy holds significant importance for early prediction of heart abnormalities. The accuracy of the extracted FECG is crucial for effective diagnosis, but the presence of external noises, particularly from the Maternal ECG (MECG), poses a major challenge in obtaining precise information. To address this issue in biomedical data processing, the study employs Finite Impulse Response (FIR) filters using an array multiplier. One notable challenge encountered in this process is the interference caused by external noises, leading to higher delay and power dissipation. In response, a modified High-Performance Multiplier (HPM) based modified booth multiplier is thoroughly reviewed and validated. This modification aims to enhance overall performance and enable high-speed operations in filtering the FECG signals. The effectiveness of these modified multipliers is assessed using ECG signal information collected from the MIT-BIH Arrhythmia Database, comprising 120 samples. In addition to noise filtering, the study explores the validation of Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) transceivers. These transceivers play a crucial role in ensuring the effective transmission of the extracted FECG signals. The research reveals a significant reduction, up to 80.4%, in both area and power dissipation during simulations conducted in Xilinx ISE 9.1 and Cadence Virtuoso. This achievement highlights the potential for improved efficiency and reliability in the processing and transmission of FECG signals, paving the way for advancements in early detection of fetal heart abnormalities.